We are looking for an experienced AI Native Solution Architect to design and scale enterprise-grade AI solutions within high-velocity, AI-native delivery pods. In this role, you will serve as a pivotal technical leader, bridging business strategy, product vision, and technical execution. You will establish architecture blueprints, select modern tech stacks, and guide cross-functional teams to build resilient, production-ready AI systems. Responsibilities End-to-End Solution Architecture: Design scalable, secure, and resilient architectures for enterprise AI systems, covering data pipelines, model integration, deployment, and monitoring Modern AI System Design: Architect advanced AI patterns, including RAG, agentic workflows, and hybrid AI architectures using vector databases and graph frameworks Strategic Product & Tech Alignment: Translate complex business goals and product roadmaps into technical specifications, architecture blueprints, and clear delivery backlogs Technical Leadership & Mentorship: Guide engineering teams on implementation best practices, design patterns, coding standards, and system maintainability Technology Evaluation & Strategy: Lead technical discovery, vendor evaluations, framework selections, and trade-off analyses (e.g., build vs. buy, open-source vs. proprietary APIs) Cross-Functional Collaboration: Partner closely with Product Leads, Engineers, Software Architects, and Business Stakeholders to ensure seamless delivery and measurable ROI Requirements Proven Track Record: 3+ years of experience as a Solution/System Architect, Principal Engineer, or Tech Lead, with demonstrated experience delivering enterprise-scale AI solutions into production Modern AI Engineering: Deep hands-on and architectural experience with modern GenAI patterns (RAG, Multi-Agent systems, function calling, tool use) and orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, Semantic Kernel) Data & Search Infrastructure: Expertise in vector databases and enterprise search/retrieval strategy Cloud & LLMOps: Strong background in cloud platforms (AWS, Azure, or Google Cloud Platform) and operationalizing models using Familiarity with LLMOps/MLOps practices Software Engineering Core: Solid background in modern backend systems engineering, microservices, API design, and distributed systems Stakeholder Bridge: Exceptional communication skills with a proven ability to translate deep technical concepts into plain language for executive stakeholders and product leaders Pragmatic Problem Solver: Comfortable navigating rapid tech evolutions, making trade-off decisions under uncertainty, and advocating for production quality Excellent command of written and spoken English (B2+ level)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 10330481
- Position Id: 5f902ded4c002fded6988f7da99e772d
- Posted 23 hours ago
